Aprajit Mahajan, Shekhar Mittal, Ofir Reich, Taha Barwahwala
{"title":"Using Machine Learning to Catch Bogus Firms","authors":"Aprajit Mahajan, Shekhar Mittal, Ofir Reich, Taha Barwahwala","doi":"10.1145/3676188","DOIUrl":"https://doi.org/10.1145/3676188","url":null,"abstract":"We investigate the use of a machine learning (ML) algorithm to identify fraudulent non-existent firms that are used for tax evasion. Using a rich dataset of tax returns in an Indian state over several years, we train an ML-based model to predict fraudulent firms. We then use the model predictions to carry out field inspections of firms identified as suspicious by the ML tool. We find that the ML model is accurate in both simulated and field settings in identifying non-existent firms. Withholding a randomly selected group of firms from inspection, we estimate the causal impact of ML driven inspections. Despite the strong predictive performance, our model driven inspections do not yield a significant increase in enforcement as evidenced by the cancellation of fraudulent firm registrations and tax recovery. We provide two explanations for this discrepancy based on a close analysis of the tax department’s operating protocols: overfitting to proxy-labels, and institutional friction in integrating the model into existing administrative systems. Our study serves as a cautionary tale for the application of machine learning in public policy contexts and of relying solely on test set performance as an effectiveness indicator. Field evaluations are critical in assessing the real-world impact of predictive models.","PeriodicalId":505364,"journal":{"name":"ACM Journal on Computing and Sustainable Societies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141811225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Connecting in Crisis: Investigating Equitable Community Internet Access in the US During the COVID-19 Pandemic","authors":"Nora Mcdonald, Lydia Stamato, Foad Hamidi","doi":"10.1145/3677326","DOIUrl":"https://doi.org/10.1145/3677326","url":null,"abstract":"Although internet access and affordability are increasingly at the center of policy decisions around issues of the “digital divide” in the US, the complex nature of usage as it relates to structural inequality is not well-understood. We partnered with Project Waves, a community internet provider, to set up connectivity across the urban landscape of a city in the Eastern United States to study factors that impact the rollout of affordable broadband internet connectivity to low-income communities during the COVID-19 pandemic. The organization endeavored to meet structural challenges, provide community support for adoption, and stave off attendant privacy concerns. We present three dimensions of equitable use prioritized by the community internet provider: safety from COVID-19 through social distancing enabled by remote access, trusted connectivity, and private internet access. We use employee interviews and a phone survey of internet recipients to investigate how the provider prioritized these dimensions and who uses their service.","PeriodicalId":505364,"journal":{"name":"ACM Journal on Computing and Sustainable Societies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141655821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Zero-configuration Alarms: Towards Reducing Distracting Smartphone Interactions while Driving","authors":"Sugandh Pargal, Neha Dalmia, Harshal R. Borse, Bivas Mitra, Sandip Chakraborty","doi":"10.1145/3675159","DOIUrl":"https://doi.org/10.1145/3675159","url":null,"abstract":"\u0000 The rising ubiquity of smartphones for navigation, driver mode, etc., has increased their use significantly among drivers; however, there are growing numbers of road fatalities being reported due to distractions from the phone while driving. In contrast to the existing solutions that use a camera or other communication media on the car or need external setups, this paper proposes a solution called\u0000 ZeCA\u0000 , where the smartphone itself can identify in real-time with zero pre-configurations whether its user is driving while engaging in a high-distraction interaction with the phone.\u0000 ZeCA\u0000 runs as a smartphone background service and generates audio-visual alerts when the phone can distract the driver. A thorough evaluation and usability study of\u0000 ZeCA\u0000 with 50 different models of vehicles driven by 70 drivers over 5 countries indicates that the proposed solution can infer distracting smartphone interactions with\u0000 \u0000 (gt 80% )\u0000 \u0000 accuracy and a\u0000 \u0000 (70% )\u0000 \u0000 reduction in smartphone usage during driving.\u0000","PeriodicalId":505364,"journal":{"name":"ACM Journal on Computing and Sustainable Societies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141656587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Speaking in Terms of Money: Financial Knowledge Acquisition via Speech Data Generation","authors":"Advait Bhat, Nidhi Kulkarni, Safiya Husain, Aditya Yadavalli, Jivat Kaur, Anurag Shukla, Monali Shelar, Vivek Seshadri","doi":"10.1145/3663775","DOIUrl":"https://doi.org/10.1145/3663775","url":null,"abstract":"Earning a living often leaves low-income individuals with little time for learning new skills, perpetuating a cycle where the need for immediate income restricts access to learning. In this study, we investigate if digital work, specifically speech data generation, can facilitate domain-specific knowledge acquisition. For the purposes of this study we focus on finance and banking. We conducted a two-week financial literacy program with low-income individuals (n=55) in Wagholi, a semi-urban area in Pune, India. Participants read aloud and recorded a nine-lesson financial curriculum, earning ₹2000 (≈ $24) for ≈ 90 minutes of voice-recording. By conducting pre- and post-tests, we found a significant increase in participants’ financial knowledge with a high effect size (cohen’s d = 1.32) and medium normalised score gain (hake’s g = 0.58). Fourteen follow-up interviews indicated the work was accessible and conveniently integrated into participants’ daily lives. Additionally, the program triggered attitude change among participants and community dialogue about critical financial concepts. Our results suggest that digital work can become an effective method for knowledge acquisition and should be tested at a larger scale.","PeriodicalId":505364,"journal":{"name":"ACM Journal on Computing and Sustainable Societies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141676129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Net Loss: An econometric method to measure the impact of Internet shutdowns","authors":"A. Tagat, Amreesh Phokeer, Hanna Kreitem","doi":"10.1145/3659466","DOIUrl":"https://doi.org/10.1145/3659466","url":null,"abstract":"The economic costs of Internet shutdowns are far-reaching and widespread, and span beyond the simple disruption to communication networks that are reliant on access to the Internet. Existing work on the impacts of the Internet shutdowns does not extensively exploit the fact that they can have adverse effects on the local economy in terms of output, employment, and investments. There is a lack of rigorous economic analysis of the impacts of shutdowns that can be more broadly applied to specific regions that account for variations in the intensity (or type) of shutdowns, as well as go beyond providing broad GDP cost estimates which may be misleading. This paper aims to bridge this gap by providing an econometric approach to estimate the impact of Internet shutdowns on GDP, employment, and foreign direct investment using panel data on 92 countries. We show that a point increase in the likelihood of an Internet shutdown was statistically significantly associated with a 15.6 percentage point reduction in the GDP per capita on average and every additional day of an Internet shutdown costs $86.58 per person on average.","PeriodicalId":505364,"journal":{"name":"ACM Journal on Computing and Sustainable Societies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140691762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Unveiling Social Anxiety: Analyzing Acoustic and Linguistic Traits in Impromptu Speech within a Controlled Study","authors":"N. K. Sahu, Manjeet Yadav, H. Lone","doi":"10.1145/3657245","DOIUrl":"https://doi.org/10.1145/3657245","url":null,"abstract":"Early detection and treatment of Social Anxiety Disorder (SAD) is crucial. However, current diagnostic methods have several drawbacks, including being time-consuming for clinical interviews, susceptible to emotional bias for self-reports, and inconclusive for physiological measures. Our research focuses on a digital approach using acoustic and linguistic features extracted from participants’ “speech” for diagnosing SAD. Our methodology involves identifying correlations between extracted features and SAD severity, selecting the effective features, and comparing classical machine learning and deep learning methods for predicting SAD. Our results demonstrate that both acoustic and linguistic features outperform deep learning approaches when considered individually. Logistic Regression proves effective for acoustic features, while Random Forest excels with linguistic features, achieving the highest accuracy of 85.71%. Our findings pave the way for non-intrusive SAD diagnosing that can be used conveniently anywhere, facilitating early detection.","PeriodicalId":505364,"journal":{"name":"ACM Journal on Computing and Sustainable Societies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140711278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Anik Sinha, Nova Ahmed, Sabbir Ahmed, Ifti Azad Abeer, Rahat Jahangir Rony, Anik Saha, Syeda Shabnam Khan, Shajnush Amir, Shabana Khan
{"title":"Roles of Technology for Risk Communication and Community Engagement in Bangladesh during COVID-19 Pandemic","authors":"Anik Sinha, Nova Ahmed, Sabbir Ahmed, Ifti Azad Abeer, Rahat Jahangir Rony, Anik Saha, Syeda Shabnam Khan, Shajnush Amir, Shabana Khan","doi":"10.1145/3648433","DOIUrl":"https://doi.org/10.1145/3648433","url":null,"abstract":"The COVID-19 pandemic required handling a clear communication of risk and community engagement. A gap is noted in scholarly studies portraying strong community engagement for risk handling, particularly in resource constrained regions in HCI community. This study covers community engagement and its use of technology during COVID-19 through a qualitative study of Bangladesh. The study looks at marginalized communities who have struggled through the pandemic yet handled the difficult time through their effective problem solving, working together as a community when there was not enough support from authorities. It is a qualitative study during the pandemic consisting of 9 communities, presenting 58 participants (N=58, Female= 33, Male=23, Transgender =2) across four divisions of Bangladesh covering urban, semi urban, and rural regions. The study uncovers the challenges and close community structures. It also shows the enhanced and increased positive role of technology during the pandemic while referring to a few communities being digitally disconnected communities that could benefit from digital connectivity in the future through increased awareness and support.","PeriodicalId":505364,"journal":{"name":"ACM Journal on Computing and Sustainable Societies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140447442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Implementing e-participation in Africa: What Roles can Public Officials Play?","authors":"P. Plantinga, N. Dlamini, Tanja Gordon","doi":"10.1145/3648438","DOIUrl":"https://doi.org/10.1145/3648438","url":null,"abstract":"A key question in e-participation is what roles public officials can play to harness the benefits of emerging technologies and practices, mitigate potential harms and, ultimately, ensure more inclusive and effective public involvement in decision-making. This paper presents results from a desktop analysis of e-participation projects from the African continent to highlight the diversity of public official roles and associated skills and perspectives that would be relevant to e-participation implementation. The identified roles and activities range from legal specialists developing guidelines to comply with personal data protection legislation, and stakeholder managers designing models of collaboration with commons-based platforms; to communications officials learning how to moderate social media conversations, and technology developers exploring new ways of verifying online identity.","PeriodicalId":505364,"journal":{"name":"ACM Journal on Computing and Sustainable Societies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139958468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"FrugalLight\u0000 : Symmetry-Aware Cyclic Heterogeneous Intersection Control using Deep Reinforcement Learning with Model Compression, Distillation and Domain Knowledge","authors":"Sachin Kumar Chauhan, Rijurekha Sen","doi":"10.1145/3648599","DOIUrl":"https://doi.org/10.1145/3648599","url":null,"abstract":"\u0000 Developing countries need to better manage fast increasing traffic flows, owing to rapid urbanization. Else, increasing traffic congestion would increase fatalities due to reckless driving, as well as keep vehicular emissions and air pollution critically high in cities like New Delhi. State-of-the-art traffic signal control methods in developed countries, however, use expensive sensing, computation and communication resources. How far can control algorithms go, under resource constraints, is explored through the design and evaluation of\u0000 FrugalLight\u0000 (FL) in this paper. We also captured and processed a real traffic dataset at a busy intersection in New Delhi, India, using efficient techniques on low cost embedded devices. This dataset (\u0000 https://delhi-trafficdensity-dataset.github.io\u0000 ) contains traffic density information at fine time granularity of one measurement every second, from all approaches of the intersection for 40 days.\u0000 FrugalLight\u0000 (\u0000 https://github.com/sachin-iitd/FrugalLight\u0000 ) is evaluated on the collected traffic dataset from New Delhi and another open source traffic dataset from New York.\u0000 FrugalLight\u0000 matches the performance of state-of-the-art Convolutional Neural Network (CNN) based sensing and Deep Reinforcement Learning (DRL) based control algorithms, while utilizing resources less by an order of magnitude. We further explore improvements using a careful combination of knowledge distillation and domain knowledge based DRL model compression, with employing Model-Agnostic Meta-Learning to quickly adapt to traffic at new intersections. The collected real dataset and\u0000 FrugalLight\u0000 therefore opens up opportunities for resource efficient RL based intersection control design for the ML research community, where the controller should have limited carbon footprint. Such intelligent, green, intersection controllers can help reduce traffic congestion and associated vehicular emissions, even if compute and communication infrastructure is limited in low resource regions. This is a critical step towards achieving two of the United Nations Sustainable Development Goals (SDG), namely sustainable cities and communities and climate action.\u0000","PeriodicalId":505364,"journal":{"name":"ACM Journal on Computing and Sustainable Societies","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139958856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}